Biology subjects

Chen, Q.

Publications and source records attributed to Chen, Q..

At least 487 records · Page 27Linked to original sources

bioRxiv2018

Functional characterization of sensory neuron membrane proteins (SNMPs)

Sensory neuron membrane proteins (SNMPs) play a critical role in the insect olfactory system but there is a deficit of functional studies beyond Drosophila. Here, we provide functional characterisation of insect SNMPs through the use of bioinformatics, genome curation, transcriptome data analysis, phylogeny, expression profiling, and RNAi gene knockdown techniques. We curated 81 genes from 35 insect species and identified a novel lepidopteran SNMP gene family, SNMP3. Phylogenetic analysis shows that lepidopteran SNMP3, but not the previously annotated lepidopteran SNMP2, is the true homologue of the dipteran SNMP2. Digital expression, microarray and qPCR analyses show that the lepidopteran SNMP1 is specifically expressed in adult antennae. SNMP2 is widely expressed in multiple tissues while SNMP3 is specifically expressed in the larval midgut. Microarray analysis suggest SNMP3 may be involved in the silkworm immunity response to virus and bacterial infections. We functionally characterised SNMP1 in the silkworm using RNAi and behavioural assays. Our results suggested that Bombyx mori SNMP1 is a functional orthologue of the Drosophila melanogaster SNMP1 and plays a critical role in pheromone detection. Split-ubiquitin yeast hybridization study shows that BmorSNMP1 has a protein-protein interaction with the BmorOR1 pheromone receptor, and the BmorOrco co-receptor. Concluding, we propose a novel molecular model in which BmorOrco, BmorSNMP1 and BmorOR1 form a heteromer in the detection of the silkworm sex pheromone bombykol.

molecular biology↗

bioRxiv2018

SPORTS1.0: a tool for annotating and profiling non-coding RNAs optimized for rRNA- and tRNA- derived small RNAs

High-throughput RNA-seq has revolutionized the process of small RNA (sRNA) discovery, leading to a rapid expansion of sRNA categories. In addition to the previously well-characterized sRNAs such as microRNAs (miRNAs), Piwi-interacting RNA (piRNAs), and small nucleolar RNA (snoRNAs), recent emerging studies have spotlighted on tRNA-derived sRNAs (tsRNAs) and rRNA-derived sRNAs (rsRNAs) as new categories of sRNAs that bear versatile functions. Since existing software and pipelines for sRNA annotation are mostly focused on analyzing miRNAs or piRNAs, here we developed the sRNA annotation pipeline optimized for rRNA- and tRNA- derived sRNAs (SPORTS1.0). SPORTS1.0 is optimized for analyzing tsRNAs and rsRNAs from sRNA-seq data, in addition to its capacity to annotate canonical sRNAs such as miRNAs and piRNAs. Moreover, SPORTS1.0 can predict potential RNA modification sites based on nucleotide mismatches within sRNAs. SPORTS1.0 is precompiled to annotate sRNAs for a wide range of 68 species across bacteria, yeast, plant, and animal kingdoms, while additional species for analyses could be readily expanded upon end users input. For demonstration, by analyzing sRNA datasets using SPORTS1.0, we reveal that distinct signatures are present in tsRNAs and rsRNAs from different mouse cell types. We also find that compared to other sRNA species, tsRNAs bear the highest mismatch rate which is consistent with their highly modified nature. SPORTS1.0 is an open-source software and can be publically accessed at https://github.com/junchaoshi/sports1.0.

bioinformatics↗

bioRxiv2018

Identification and prioritization of gene sets associated with schizophrenia risk by co-expression network analysis in human brain

Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. The main purpose of this study was to identify and prioritize co-expressed gene sets in a hierarchical manner, based on the strength of the relationships with clinical diagnosis and with the polygenic risk for schizophrenia. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to RNA-quality adjusted DLPFC RNA-Seq data from the LIBD Postmortem Human Brain Repository (90 controls, 74 schizophrenia; Caucasians) to construct co-expression networks and detect modules of co-expressed genes. After internal and external validation, modules of selected interest were tested for enrichment in biological ontologies, association with schizophrenia polygenic risk scores (PRS), with diagnosis and for enrichment in genes within the significant GWAS loci reported by the Psychiatric Genomic Consortium (PGC2). The association between schizophrenia genetic signals and modules of co-expression converged on one module showing a significant association with diagnosis, PRS and significant overlap with 36 PGC2 loci genes, deemed as tier 1 (strongest candidates for drug targets). Fifty-three PGC2 loci genes were in modules associated only with diagnosis (tier 2) and 59 in modules unrelated to diagnosis or PRS (tier 3). In conclusion, our study highlights complex relationships between gene co-expression networks in the brain and polygenic risk for SCZ and provides a strategy for using this information in selecting potentially targetable gene sets for therapeutic drug development.

neuroscience↗

bioRxiv2018

Single-trial Phase Entrainment of Theta Oscillations in Sensory Regions Predicts Human Associative Memory Performance

Episodic memories are rich in sensory information and often contain integrated information from different sensory modalities. For instance, we can store memories of a recent concert with visual and auditory impressions being integrated in one episode. Theta oscillations have recently been implicated in playing a causal role synchronizing and effectively binding the different modalities together in memory. However, an open question is whether momentary fluctuations in theta synchronization predict the likelihood of associative memory formation for multisensory events. To address this question we presented movies and sounds with their luminance and volume modulated at theta (4 Hz), with a phase offset at 0{degrees} or 180{degrees} with respect to each other. This allowed us to entrain the visual and auditory cortex in a synchronous (0{degrees}) or asynchronous manner (180{degrees}). Participants were asked to remember the association between a movie and a sound while having their EEG activity recorded. Associative memory performance was significantly enhanced in the synchronous (0{degrees}) compared to the asynchronous (180{degrees}) condition. Source-level analysis demonstrated that the physical stimuli effectively entrained their respective cortical areas with a corresponding phase offset. Importantly, the strength of entrainment during encoding correlated with the efficacy of associative memory such that small phase differences between visual and auditory cortex predicted a high likelihood of correct retrieval in a later recall test. These findings suggest that theta oscillations serve a specific function in the episodic memory system: Binding the contents of different modalities into coherent memory episodes.\n\nSignificance StatementHow multi-sensory experiences are bound to form a coherent episodic memory representation is one of the fundamental questions in human episodic memory research. Evidence from animal literature suggests that the relative timing between an input and theta oscillations in the hippocampus is crucial for memory formation. We precisely controlled the timing between visual and auditory stimuli and the neural oscillations at 4 Hz using a multisensory entrainment paradigm. Human associative memory formation depends on coincident timing between sensory streams processed by the corresponding brain regions. We provide evidence for a significant role of relative timing of neural theta activity in human episodic memory on a single trial level, which reveals a crucial mechanism underlying human episodic memory.

neuroscience↗

bioRxiv2018

Loss of SDHB reprograms energy metabolisms and inhibits high fat diet induced metabolic syndromes

Mitochondrial respiratory complex II utilizes succinate, key substrate of the Krebs cycle, for oxidative phosphorylation, which is essential for glucose metabolism. Mutations of complex II cause cancers and mitochondrial diseases, raising a critical question of the (patho-)physiological functions. To address the fundamental role of complex II in systemic energy metabolism, we specifically knockout SDHB in mice liver, a key complex II subunit that tethers the catalytic SDHA subunit and transfers the electrons to ubiquinone, and found that SHDB deficiency abolishes the assembly of complex II without affecting other respiration complexes while largely retaining SDHA stability. SHDB ablation reprograms energy metabolism and hyperactivates the glycolysis, Krebs cycle and {beta}-oxidation pathways, leading to catastrophic energy deficit and early death. Strikingly, sucrose supplementation or high fat diet resumes both glucose and lipid metabolism and prevent early death. Also, SDHB deficient mice are completely resistant to high fat diet induced obesity. Our findings reveal that the unanticipated role of complex II orchestrating both lipid and glucose metabolisms, and suggest that SDHB is an ideal therapeutic target for combating obesity.

molecular biology↗

bioRxiv2018

Elongator is required for root stem cell maintenance by regulating SHORT ROOT transcription

SHORTROOT (SHR) is essential for stem cell maintenance and radial patterning in Arabidopsis thaliana roots, but how its expression is regulated is still unknown. Here, we report that Elongator regulates the transcription of SHR. The depletion of Elongator drastically reduced SHR expression and led to defective root stem cell maintenance and radial patterning. The importance of the nuclear localization of Elongator for its functioning, together with the insensitivity of the elp1 mutant to the transcription elongation inhibitor 6-azauracil and the direct interaction of the ELP4 subunit with the C-terminal domain of RNA polymerase II (RNAPII CTD), support the notion that Elongator plays important roles in transcription elongation. Indeed, we found that ELP3 associates with the pre-mRNA of SHR and that mutation of Elongator reduces the enrichment of RNAPII on the SHR gene body. Moreover, Elongator interacted in vivo with SUPPRESSOR OF Ty4 (SPT4), a well-established transcription elongation factor that was recruited to the SHR locus. Together, these results demonstrate that Elongator acts in concert with SPT4 to regulate the transcription of SHR.

plant biology↗

bioRxiv2018

Structural and functional influences of urban and rural childhoods on the medial prefrontal cortex

Global increases in urbanization have brought dramatic economic, environmental and social changes. However, less is understood about how these may influence disease-related brain mechanisms underlying epidemiological observations that urban birth and childhoods may increase the risk for neuropsychiatric disorders, including increased social stress and depression. In a genetically homogeneous Han Chinese adult population with divergent urban and rural birth and childhoods, we examined the structural and functional MRI neural correlates of childhood urbanicity, focusing on behavioral traits responding to social status threats, and polygenic risk for depression. Subjects with divergent rural and urban childhoods were similar in adult socioeconomic status and were genetically homogeneous. Urban childhoods, however, were associated with higher trait anxiety-depression. On structural MRI, urban childhoods were associated with relatively reduced medial prefrontal gray matter volumes. Functional medial prefrontal engagement under social status threat during working memory correlated with trait anxiety-depression in subjects with urban childhoods, to a significantly greater extent than in their rural counterparts, implicating an exaggerated physiological response to the threat context. Stress-associated medial prefrontal engagement also interacted with polygenic risk for depression, significantly predicting a differential response in individuals with urban but not rural childhoods. Developmental urbanicity thus differentially influenced medial prefrontal structure and function, at least in part through mechanisms associated with the neural processing of social status threat, trait anxiety, and genetic risk for depression, which may be factors in the association of urbanicity with adult psychopathology.\n\nSignificance StatementUrban living has been associated with social inequalities and stress. However, less is understood about the neural underpinnings by which these stressors affect disease risk, and in particular, genetic risk for depression. Leveraging urbanization in China, we studied adults with diverse urban and rural upbringings, who were genetically homogeneous and with similar current socioeconomic status, to isolate the effects of childhood urbanicity. At medial prefrontal cortex, a region critical for processing emotional stressors and social status, genetic risk for depression resulted in more deleterious function under stress in individuals with urban, but not rural childhoods. This implicates medial prefrontal cortexs critical role in brain development, integrating genetic mechanisms of stress and depression with the childhood environment.

neuroscience↗

bioRxiv2017

Tracking the dynamic functional connectivity structure of the human brain across the adult lifespan

The transition from early adulthood to older is marked by pronounced functional and structural brain transformations that impact cognition and behaviour. Here, we use dynamic functional network connectivity method to examine resting state functional network changes over aging process. In general, the features of dynamic functional states are generally varying across ages, such as the frequency of expression and the amount of time spent in the certain state. Increasing age is associated with less variability of functional state across time at rest period. From age point of view, examining the age-related difference of topology index revealed 19-30 age range has the significant largest global efficiency, largest local efficiency of default-mode network (DMN), cognitive control network (CCN) and salience network (SN). As for functional states, one state displayed the whole positive connectivity, in the meantime, it has the largest global efficiency and local efficiency of three subnetworks. Besides, the frequency of another state was negatively correlated to the box block (The Wechsler Adult Intelligence Scale subset, which is thought to evaluate fine motor skills, processing speed, and visuospatial ability), while positively correlated with age, and the box block was inversely correlated to age. The results suggested that cognitive aging may be characterized by the dynamic functional network connectivity. Taken together, these findings suggested the importance of a dynamic approach to understanding cognitive aging in lifespan.

neuroscience↗

bioRxiv2017

Small Molecule Inhibitors of the Human Histone Lysine Methyltransferase NSD2 / WHSC1 / MMSET Identified from a Quantitative High-Throughput Screen with Nucleosome Substrate

The activity of the histone lysine methyltransferase NSD2 is thought to play a driving role in oncogenesis. Both overexpression of NSD2 and point mutations that increase its catalytic activity are associated with a variety of human cancers. While NSD2 is an attractive therapeutic target, no potent, selective and cell-active inhibitors have been reported to date, possibly due to the challenging nature of developing high-throughput assays for NSD2. To establish a platform for the discovery and development of selective NSD2 inhibitors, multiple assays were optimized and implemented. Quantitative high-throughput screening was performed with full-length wild-type NSD2 and a nucleosome substrate against a diverse collection of known bioactives comprising 16,251 compounds. Actives from the primary screen were further interrogated with orthogonal and counter assays, as well as activity assays with the clinically relevant NSD2 mutants E1099K and T1150A. Five confirmed inhibitors were selected for follow-up, which included a radiolabeled validation assay, surface plasmon resonance studies, methyltransferase profiling, and histone methylation in cells. The identification of NSD2 inhibitors that bind the catalytic SET domain and demonstrate activity in cells validates the workflow, providing a template for identifying selective NSD2 inhibitors.

cancer biology↗

bioRxiv2017

DirtyGenes: significance testing for gene or bacterial population composition changes using the Dirichlet distribution

High throughput sequencing, and quantitative polymerase chain reaction (qPCR), can detect changes in bacterial communities or the genes that they carry, between different environments or treatments. These methods are applied widely to microbiomes in humans, animals, soil and water; an important application is for changes in antimicrobial resistance genes (ARGs). However, at present, there is no statistical method to determine whether observed changes in the overall composition are significant, or result from random variations between samples. Therefore researchers are limited to graphical descriptions. We describe a novel statistical method to determine whether or not observed differences in bacterial populations or their genes are significant. It can be used with data from shotgun metagenomics, 16S characterisation or qPCR. It can also be used for experimental design, to calculate the number of samples needed in future experiments. We show its application to two example data sets. The first is published data on bacterial communities and ARGs in the environment, in which we show that there are significant changes in both ARG and community composition. The second is a new data set on seasonality in bacterial communities and ARGs in hooves from four sheep. While the observed differences are not significant, we show that a minimum group size of eight sheep in a future experiment would provide sufficient power to observe significant changes, should the already observed changes be true. This method has broad uses for statistical testing and experimental design in experiments on changing microbiomes, including for studies on antimicrobial resistance.

bioinformatics↗

bioRxiv2017

Identification of Cancer-associated Metabolic Vulnerabilities by Modeling Multi-objective Optimality in Metabolism

Computational modeling of the genome-wide metabolic network is essential for designing new therapeutics targeting cancer-associated metabolic disorder, which is a hallmark of human malignancies. However, previous studies generally assumed that metabolic fluxes of cancer cells are subjected to the maximization of biomass production, despite the wide existence of trade-offs among multiple metabolic objectives. To address this issue, we developed a multi-objective model of cancer metabolism with algorithms depicting approximate Pareto surfaces and incorporating multiple omics datasets. To validate this approach, we built individualized models for NCI-60 cancer cell lines, and accurately predicted cell growth rates and other biological consequences of metabolic perturbations in these cells. By analyzing the landscape of approximate Pareto surface, we identified a list of metabolic targets essential for cancer cell proliferation and the Warburg effect, and further demonstrated their close association with cancer patient survival. Finally, metabolic targets predicted to be essential for tumor progression were validated by cell-based experiments, confirming this multi-objective modelling method as a novel and effective strategy to identify cancer-associated metabolic vulnerabilities.

systems biology↗

bioRxiv2017

The contribution of common genetic risk variants for ADHD to a general factor of childhood psychopathology

Attention-deficit/hyperactivity disorder (ADHD) is a heritable neurodevelopmental disorder, with common genetic risk variants implicated in the clinical diagnosis and symptoms of ADHD. However, given evidence of comorbidity and genetic overlap across neurodevelopmental and externalizing conditions, it remains unclear whether these genetic risk variants are ADHD-specific. The aim of this study was to evaluate the associations between ADHD genetic risks and related neurodevelopmental and externalizing conditions, and to quantify the extent to which any such associations can be attributed to a general genetic liability towards psychopathology. We derived ADHD polygenic risk scores (PRS) for 13,460 children aged 9 and 12 years from the Child and Adolescent Twin Study in Sweden, using results from an independent meta-analysis of genome-wide association studies of ADHD diagnosis and symptoms. Associations between ADHD PRS, a latent general psychopathology factor, and six latent neurodevelopmental and externalizing factors were estimated using structural equation modelling. ADHD PRS were statistically significantly associated with elevated levels of inattention, hyperactivity/impulsivity, autistic traits, learning difficulties, oppositional-defiant, and conduct problems (standardized regression coefficients=0.07-0.12). Only the association with specific hyperactivity/impulsivity remained significant after accounting for a general psychopathology factor, on which all symptoms loaded positively (standardized mean loading=0.61, range=0.32-0.91). ADHD PRS simultaneously explained 1% (p-value<0.001) of the variance in the general psychopathology factor and 0.50% (p-value<0.001) in the specific hyperactivity/impulsivity factor. Our results suggest that common genetic risk variants associated with ADHD have largely general pleiotropic effects on neurodevelopmental and externalizing traits in the general population, in addition to a specific association with hyperactivity/impulsivity symptoms.

genetics↗

bioRxiv2017

Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide

Subcortical brain structures are integral to motion, consciousness, emotions, and learning. We identified common genetic variation related to the volumes of nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus, using genome-wide association analyses in over 40,000 individuals from CHARGE, ENIGMA and the UK-Biobank. We show that variability in subcortical volumes is heritable, and identify 25 significantly associated loci (20 novel). Annotation of these loci utilizing gene expression, methylation, and neuropathological data identified 62 candidate genes implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

genetics↗

bioRxiv2017

Structural and functional MRI from a cross-sectional Southwest University Adult lifespan Dataset (SALD)

Recently, the field of developmental neuroscience has aimed to uncover the developmental trajectory of the human brain and understand the changes that occur as a function of aging. Here we present an adult lifespan dataset of functional magnetic resonance imaging (fMRI) data including structural MRI and resting-state functional MRI. 494 healthy adults (age range: 19-80 years; Males=187) were recruited and completed two multi-modal MRI scan sessions in the Brain Imaging Central of Southwest University, Chongqing, China. The goals of the dataset are to give researchers the opportunity to map the developmental trajectory of structural and functional changes of human brain and to replicate previous findings.

neuroscience↗

bioRxiv2017

SLFL Genes Participate in the Ubiquitination and Degradation of S-RNase in Self-Compatible Chinese Peach

The gametophytic self-incompatibility (SI) mediated by S-RNase of Rosaceae, Solanaceae and Plantaginaceae, is controlled by two tightly linked genes located at highly polymorphic S-locus: the S-RNase for pistil specificity and the F-box gene (SFB/SLF) for pollen specificity, respectively. The F-box gene of peach (Prunus persica) is S haplotype-specific F-box (SFB). In this study, we selected 37 representative varieties according to the evolution route of peach and identified their S genotypes. We cloned pollen determinant genes mutant PperSFB1m, PperSFB2m, PperSFB4m and normal PperSFB2, and style determinant genes S1-RNase, S2-RNase, S2m-RNase and S4-RNase. Mutant PperSFBs were translated terminated prematurely because of fragment insertion. Yeast two-hybrid showed that mutant PperSFBs and normal PperSFB2 interacted with all S-RNases. Normal PperSFB2 was divided into four parts: box, box-V1, V1-V2 and HVa-HVb. Protein interaction analyses showed that the box portion did not interact with S-RNases, both of the box-V1 and V1-V2 had interactions with S-RNases, while the hypervariable region of PperSFB2 HVa-HVb only interacted with S2-RNase. Bioinformatics analysis of peach genome revealed that there were other F-box genes located at S-locus, and of which three F-box genes were specifically expressed in pollen, namely PperSLFL1, PperSLFL2 and PperSLFL3, respectively. Phylogenetic analysis showed that PperSFBs and PperSLFLs were classified into two different clades. Yeast two-hybrid analysis revealed that as with PperSFBs, the three F-box proteins interacted with PperSSK1. Yeast two-hybrid and BiFC showed that PperSLFLs interacted with S-RNases with no allelic specificity. In vitro ubiquitination assay showed that PperSLFLs could tag ubiquitin molecules to PperS-RNases. In all, the above results suggest that three PperSLFLs are the appropriate candidates for the general inhibitor, which would inactivate the S-RNases in pollen tubes, and the role of three PperSLFL proteins is redundant, as S-RNase repressors involved in the self-incompatibility of peach.

molecular biology↗

bioRxiv2017

Placental gene expression mediates the interaction between obstetrical history and genetic risk for schizophrenia

Defining the environmental context in which genes enhance susceptibility can provide insight into the pathogenesis of complex disorders, like schizophrenia. Here we show that the intrauterine and perinatal environment modulates the association of schizophrenia with genomic risk, as measured with polygenic risk scores (PRS) based primarily on GWAS significant variants. Genomic risk interacts with intrauterine and perinatal complications (Early Life Complications, ELCs) in each of three independent samples from USA, Italy and Germany (overall n= 1693, p= 6e-05). In each sample, the liability of schizophrenia explained by PRS is nominally more than five times greater in the presence of a history of ELCs compared with its absence. In each sample, patients with positive ELC histories have higher PRS than patients without ELCs, which is further confirmed in two additional patient samples from Germany and Japan (overall n=2038, p= 1e-04). The gene set based on the schizophrenia loci interacting with ELCs is highly expressed in multiple placental compartments and dynamically regulated in placenta from complicated in comparison with normal pregnancies. The same genes are differentially up-regulated in placentae from male compared with female offspring. The interaction between genomic risk and ELCs is mainly driven by GWAS significant loci enriched for genes highly expressed in the various placenta samples. Molecular pathway analyses based on the genes not driving this interaction reflect previous analyses about schizophrenia risk-genes, while genes highly and differentially expressed in placentae implicate an orthogonal biology involving cellular stress. These results suggest that the most significant genetic variants detected by current schizophrenia GWAS contribute to risk in part by converging on a developmental trajectory sensitive to events affecting placentation, which may underlie the male preponderance of schizophrenia and offer new insights into primary prevention.

genetics↗

bioRxiv2017

Developmental And Genetic Regulation Of The Human Cortex Transcriptome In Schizophrenia

GWAS have identified 108 loci that confer risk for schizophrenia, but risk mechanisms for individual loci are largely unknown. Using developmental, genetic, and illness-based RNA sequencing expression analysis, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and post-natal life. We found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this eQTL database to show that 48.1% of risk variants for schizophrenia associated with nearby expression. Within patients and controls, we implemented a novel algorithm for RNA quality adjustment, and identified 237 genes significantly associated with diagnosis that replicated in an independent case-control dataset. These genes implicated synaptic processes and were strongly regulated in early development (p < 10-20). These data offer new targets for modeling schizophrenia risk in cellular systems.

neuroscience↗

bioRxiv2017

De novo BK channel mutation causes epilepsy by regulating voltage-dependent, but not calcium-dependent, activation

Epilepsy is one of the most common neurological diseases. Here we report the first de novo mutation in the BK channel (p.N995S) that causes epilepsy in two independent families. The p.N995S mutant channel showed a markedly increased macroscopic potassium current mediated by increases in both channel open probability and channel open dwell time. Mutation p.N995S affects the voltage-activation pathway of BK channel, but does not affect the calcium sensitivity. Paxilline blocks potassium currents from both WT and mutant BK channels. We also identified two variants of unknown significance, p.E656A and p.N1159S in epilepsy patients. However, they do not affect BK channel functions, therefore, are unlikely to be a cause of disease. These results expand the BK channelopathy to a more common disease of epilepsy, suggest that the BK channel is a drug target for treatment of epilepsy, and highlight the importance of functional studies in the era of precision medicine.

biophysics↗